Detailed Project Description

Today, we are experiencing rapid growth in the amount of medical data collected - full genome sequencing, microbiome data, etc - and this presents an opportunity for machine learning algorithms to significantly improve health care. However, the current services require you to upload your medical data in clear text (unacceptable with regards to privacy) and lacks proper bench-marking. We introduce Trustless.Health, a decentralised and transparent platform for machine analysis of medical data based on top of Ethereum. We also present fhe-wasm, a WebAssembly interpreter with support for full homomorphic encryption, that backs all models on Trustless.Health meaning no user data (including the results of the analysis!) is ever revealed to the model service providers.

Tech Stack

The core of Trustless.Health is the compute engine which runs all models using fully homomorphic encryption. To make sure the platform would support as many languages as possible, an interpreter, written on top of NuCypher's nuFHE package, was achieved that can execute models compiled for WebAssembly under FHE. In the rust-example directory, we show how a DNA analysis model written in Rust is compiled to WASM and then executed on encrypted input data using fhe-wasm.

The front-end, hosted at https://trustless.health, is a React/Redux DApp written in typescript with ts-lint for strong type-safety. The web app uses axios to query a local Python server, which uses the nuFHE package to generate encryption keys as well as encrypting/decrypting of messages. Users should run this locally (see the client-server directory). The webapp is web3 compatible and should work out of the box with Metamask.